This chapter describes a second-order adaptive network model for mental processes making use of shared mental models (SMM) for team performance. The chapter illustrates on the one hand the value of adequate SMM’s for safe and efficient team performance and on the other hand in cases of imperfections of such shared team models how this complicates the team performance. To this end, the adaptive network model covers use, adaptation and control of the shared mental model. It is illustrated for an application context of a medical team performing a tracheal intubation, executed by a nurse and a medical specialist. Simulations illustrate how the adaptive network model is able to address the type of complications that can occur in realistic scenarios.

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This article presents the use of second-order adaptive network models of hospital teams consisting of doctors and nurses, interacting together. A variety of scenarios are modelled and simulated, in relation with respiratory distress of a neonate, along with the integration of an AI-Coach for monitoring and support of such teams and of organizational learning. The research highlights the benefits of introducing a virtual AI-Coach in a hospital setting. The practical application setting revolves around a medical team responsible for managing neonates with respiratory distress. In this setting an AI-Coach act as an additional team member, to ensure correct execution of medical procedure. Through simulation experiments, the adaptive network models demonstrate that the AI-Coach not only aids in maintaining correct medical procedure execution but also facilitates organizational learning, leading to significant improvements in procedure adherence and error reduction during neonatal care.

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Within organisational learning literature, mental models are considered a vehicle for both individual learning and organisational learning. By learning individual mental models (and making them explicit), a basis for formation of shared mental models for the level of the organisation is created, which after its formation can then be adopted by individuals. This provides mechanisms for organisational learning. These mechanisms have been used as a basis for an adaptive computational network model. The model is illustrated by a not too complex but realistic case study.@en

Multilevel organisational learning concerns an interplay of different types of learning at individual, team, and organisational levels. These processes use complex dynamic and adaptive mechanisms. A second-order adaptive network model for this is introduced here and illustrated.@en

This paper describes an extension of a safety culture within hospital organizations providing more transparency and acknowledgement of all actors, and in particular the parents. It contributes a model architecture to support a hospital to develop such an extended safety culture. It is illustrated for prevention of postpartum depression. Postpartum depression is a commonly known consequence of childbirth for both mothers and fathers. In this research, we computationally analyze the risk factors and lack of support received by fathers. Therefore, we use shared mental models to model the effects of poor and additional communication by healthcare practitioners to mitigate the development of postpartum depression in both the mother and the father. Both individual mental models and shared mental models are considered in the design of the computational model. The paper illustrates the benefits of simple support in terms of communication during childbirth, which has lasting effects, even outside the hospital. For the impact of additional communication, a Virtual Safety Coach is designed that intervenes when necessary to provide support, i.e., when a health care practitioner doesn't. Moreover, organizational learning is also modelled to improve the mental models of both the Safety Coach and the Health Care Practitioner.@en

This chapter describes a second-order adaptive network model for mental processes making use of shared mental models (SMM) for team performance. The chapter illustrates on the one hand the value of adequate SMM’s for safe and efficient team performance and on the other hand in cases of imperfections of such shared team models how this complicates the team performance. To this end, the adaptive network model covers use, adaptation and control of the shared mental model. It is illustrated for an application context of a medical team performing a tracheal intubation, executed by a nurse and a medical specialist. Simulations illustrate how the adaptive network model is able to address the type of complications that can occur in realistic scenarios.

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Multilevel organizational learning concerns an interplay of different types of learning at individual, team, and organizational levels. These processes use complex dynamic and adaptive mechanisms. A second-order adaptive network model for this is introduced here and illustrated.@en

Religion is an important aspect of many individuals’ lives. A central element of it is a mental God-model. Such a mental God-model can have different forms and depending on that it has a specific influence on human behaviour. This has been extensively studied from different perspectives. The current study uses a number of these perspectives as a basis for an integrative adaptive network model for formation and use of a mental God-model. It describes the mental states involved, their mutual relations, and the adaptation of some of these relations over time due to learning. Based on the obtained network model, simulations can be done for almost any kind of religion and person, showing different behaviours for persons with different religious backgrounds and characters. The focus here was mainly on the very relevant topic of the influence of religion on human empathy and disempathy. The developed adaptive network model can be valuable for many uses, involving support for a better understanding, and even prediction, of the behaviour of religious individuals and its underlying mechanisms. It is illustrated for a number of different scenarios for different types of persons and religions.@en

Within organisational learning literature, mental models are considered a vehicle for both individual learning and organizational learning. By learning individual mental models (and making them explicit), a basis for formation of shared mental models for the level of the organization is created, which after its formation can then be adopted by individuals. This provides mechanisms for organizational learning. These mechanisms have been used as a basis for an adaptive computational network model. The model is illustrated by a not too complex but realistic case study.@en

This paper describes a network model for mental processes making use of shared mental models (SMM) of team performance. The paper illustrates the value of adequate SMM’s for safe and efficient team performance. The addressed application context is that of a medical team performing a tracheal intubation executed by a nurse and a medical specialist. Simulations of successful and unsuccessful team performance have been performed, some of which are presented. The paper discusses potential further elaborations for future research as well as implications for other domains of team performance.

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This paper describes a second-order adaptive network model for mental processes making use of shared mental models for team performance. The paper illustrates the value of adequate shared mental models for safe and efficient team performance and in cases of imperfections of such shared team models how this complicates the team performance. It is illustrated for a context of a medical team performing a tracheal intubation. Simulations illustrate how the adaptive network model is able to address the type of complications that can occur in realistic scenarios.

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